住院跌倒病人跌倒傷害預測模式之探討;The Prediction Models of Falls Injury among Hospitalized Patients

MUIR > Seminar > 2013 International Conference on Health Care and Health Industry > Item 987654321/2420

Please use this identifier to cite or link to this item: http://ir.meiho.edu.tw/ir/handle/987654321/2420

Title:	住院跌倒病人跌倒傷害預測模式之探討;The Prediction Models of Falls Injury among Hospitalized Patients
Authors:	馬秀玲;許弘毅;陳幼梅
Keywords:	跌倒傷害;類神經網路;邏輯式迴歸;全域敏感度分析
Date:	2013
Issue Date:	2014-04-21T08:32:51Z (UTC)
Abstract:	跌倒事件在醫院為高危險性且經常發生的問題。本研究目的在透過運用類神經網路(ANN)分析模式及邏輯斯迴歸(MLR)分析模式找出造成跌倒傷害的重要影響因子，提供給醫護人員更有效的篩選出需特別注意照護的病人。研究結果顯示使用12 個重要變項預測住院跌倒病人跌倒傷害的準確性，以ANN 分析模式優於MLR 分析模式，利用全域敏感度分析(Global Sensitivity Analysis )評估影響住院病人跌倒傷害各個預測因子之權重方面，最重要的因子為步態與平衡障礙，次之為服用嗎啡類複方止痛藥及高年齡者。
Appears in Collections:	[Seminar] 2013 International Conference on Health Care and Health Industry

Files in This Item:

There are no files associated with this item.

View Licence